作者: Miquel Duran-Frigola , Eduardo Pauls , Oriol Guitart-Pla , Martino Bertoni , Víctor Alcalde
DOI: 10.1101/745703
关键词: Drug discovery 、 Chemical similarity 、 Biological network 、 Identification (biology) 、 Small molecule 、 Chemical descriptors 、 Computational biology 、 Similarity (network science)
摘要: We present the Chemical Checker (CC), a resource that provides processed, harmonized and integrated bioactivity data on 800,000 small molecules. The CC divides into five levels of increasing complexity, ranging from chemical properties compounds to their clinical outcomes. In between, it considers targets, off-targets, perturbed biological networks several cell-based assays such as gene expression, growth inhibition morphological profilings. CC, are expressed in vector format, which naturally extends notion similarity between similarities signatures different kinds. show how can boost performance drug discovery tasks typically capitalize descriptors, including target identification library characterization. Moreover, we demonstrate experimentally validate be used reverse mimic disease models genetic perturbations, options otherwise impossible using information alone.